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Django app to provide a JS agnostic way to work with charts.

Project description

Graphos
----------------

[![Build Status](https://travis-ci.org/agiliq/django-graphos.png)](https://travis-ci.org/agiliq/django-graphos)

Graphos is a Django app to plot data into a live graph.

### Supported Backends:

* Python Nested lists
* CSV Files
* MongoDB
* Redis
* Django ORM

### Charting API Supported

* [Flot](http://flotcharts.org)
* [Google Charts API](https://developers.google.com/chart/)
* [YUI Charts](http://yuilibrary.com/yui/docs/charts/)
* [Morris.js](http://www.oesmith.co.uk/morris.js/)
* [Highcharts](http://www.highcharts.com/)

### Chart types supported

#### Flot

* Line chart
* Bar Chart
* Point Chart

#### Google Charts

* Line chart
* Column chart
* Bar chart
* Candlestick charts
* Pie chart

#### YUI

* Line chart
* Column chart
* Bar chart
* Pie chart

#### Morris.js

* Line chart
* Column chart
* Donut chart

#### Highcharts

(You will need to buy a license if you use highcharts for commerical use)

* Line Chart
* Bar Chart
* Column Chart
* Pie Chart



### Demo

Install the requirements, `manage.py runserver`.
The installed demo app shows the various suported chart types.


### Overview of Plot generation

Generating a plot requires two things. A DataSource and a Chart object.

In your view, you do something like this:

data = [
['Year', 'Sales', 'Expenses'],
[2004, 1000, 400],
[2005, 1170, 460],
[2006, 660, 1120],
[2007, 1030, 540]
]
Chart = LineChart(SimpleDataSource(data=data), html_id="line_chart")

And then in the template:

{{ chart.as_html }}


### Examples

#### Generating a plot from python list

data = [
['Year', 'Sales', 'Expenses'],
[2004, 1000, 400],
[2005, 1170, 460],
[2006, 660, 1120],
[2007, 1030, 540]
]
Chart = LineChart(SimpleDataSource(data=data))

#### Generating a plot from CSV file

csv_file = open("hello.csv")
LineChart(CSVDataSource(csv_file))

#### Generating a plot from the ORM

queryset = Accounts.objects.filter(foo=bar)
LineChart(ModelDataSource(queryset, fields=["year", "sales", "expenses"]))


#### Generating a plot from Redis
Todo

#### Generating a plot from MongoDB
Todo

### Installation
Todo - need to publish the app at Pypi after competion


### Creating new DataSource

A DataSource is a class which has these three methods.

get_data
get_header
get_first_column

`get_header` is used by a `Renderer` to create the labels.
`get_first_column` is used to set the x axis labels
`get_data` is used to get the data for display. It should always return a nested list. Eg:

[
['Year', 'Sales', 'Expenses'],
[2004, 1000, 400],
[2005, 1170, 460],
[2006, 660, 1120],
[2007, 1030, 540]
]

If you create a class extending `SimpleDataSource`, and implement `get_data`. You get
`get_header` and `get_first_column` for free.

### Creating new Renderer

A renderer is a class which takes a `DataSource` and can convert it to the html to display.

The only required method on a `Renderer` is `as_html`. This will convert the dat ato a format which can display the chart.

Generally you will convert the data to json and pass it to the template which you return.


### License

BSD

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